msi_processor.sensors package

Sensor adaptation layer (C-SENSORS).

Externalises all sensor-specific data (band set, radiometric depth, GSD, ADF bindings) so the generic processing chain stays sensor-agnostic: a new sensor is a new profile plus private ADFs, with no core change (REQ-AD-01, REQ-D-07). This package contains no instrument constants in code and no algorithm code (REQ-D-04); private calibration values live only in the ADFs, which the profile references by URI (REQ-S-01/05).

Submodules

msi_processor.sensors.profile module

Typed sensor profile (C-SENSORS; SDD <5.4.12>, ICD <5.3.6>).

A minimal, schema-validated SensorProfile specialising the generic chain for one instrument. It carries references to the private calibration ADFs (by id → URI) and never embeds private calibration values (REQ-AD-01, REQ-S-01/05). The loader load_profile() reads a profile JSON instance and validates it.

Trace: REQ-AD-01..04, REQ-DAT-03; ICD-IF-PROF-*.

class msi_processor.sensors.profile.BandSpec(**data)

Bases: BaseModel

One spectral band of the sensor (data only, no private values).

Attributes:

model_extra

Get extra fields set during validation.

model_fields_set

Returns the set of fields that have been explicitly set on this model instance.

Methods

copy(*[, include, exclude, update, deep])	Returns a copy of the model.
model_construct([_fields_set])	Creates a new instance of the Model class with validated data.
model_copy(*[, update, deep])	rtype: Self
model_dump(*[, mode, include, exclude, ...])	rtype: dict[str, Any]
model_dump_json(*[, indent, ensure_ascii, ...])	rtype: str
model_json_schema([by_alias, ref_template, ...])	Generates a JSON schema for a model class.
model_parametrized_name(params)	Compute the class name for parametrizations of generic classes.
model_post_init(context, /)	Override this method to perform additional initialization after __init__ and model_construct.
model_rebuild(*[, force, raise_errors, ...])	Try to rebuild the pydantic-core schema for the model.
model_validate(obj, *[, strict, extra, ...])	Validate a pydantic model instance.
model_validate_json(json_data, *[, strict, ...])	rtype: Self
model_validate_strings(obj, *[, strict, ...])	Validate the given object with string data against the Pydantic model.

construct
dict
from_orm
json
parse_file
parse_obj
parse_raw
schema
schema_json
update_forward_refs
validate

center_wavelength_nm: Optional[float]

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

name: str

class msi_processor.sensors.profile.SensorProfile(**data)

Bases: BaseModel

Per-sensor configuration (SDD <5.4.12>).

Parameters:

profile_id, profile_version, sensor_id:

Identity of the profile instance.

bands:

Ordered list of BandSpec (at least one).

bit_depth:

Sensor radiometric depth; valid DN range [0, 2**bit_depth - 1] (DPM-PRM-GEN-01, default 12).

gsd:

Nominal ground sampling distance in metres.

adf_bindings:

Mapping of ADF id → URI reference. Private calibration content is resolved from these URIs at run time and is never stored in the profile (REQ-S-01/05).

Attributes:

band_names

Return the band ids in declaration order.

model_extra

Get extra fields set during validation.

model_fields_set

Returns the set of fields that have been explicitly set on this model instance.

Methods

copy(*[, include, exclude, update, deep])	Returns a copy of the model.
model_construct([_fields_set])	Creates a new instance of the Model class with validated data.
model_copy(*[, update, deep])	rtype: Self
model_dump(*[, mode, include, exclude, ...])	rtype: dict[str, Any]
model_dump_json(*[, indent, ensure_ascii, ...])	rtype: str
model_json_schema([by_alias, ref_template, ...])	Generates a JSON schema for a model class.
model_parametrized_name(params)	Compute the class name for parametrizations of generic classes.
model_post_init(context, /)	Override this method to perform additional initialization after __init__ and model_construct.
model_rebuild(*[, force, raise_errors, ...])	Try to rebuild the pydantic-core schema for the model.
model_validate(obj, *[, strict, extra, ...])	Validate a pydantic model instance.
model_validate_json(json_data, *[, strict, ...])	rtype: Self
model_validate_strings(obj, *[, strict, ...])	Validate the given object with string data against the Pydantic model.

construct
dict
from_orm
json
parse_file
parse_obj
parse_raw
schema
schema_json
update_forward_refs
validate

adf_bindings: dict[str, str]

property band_names: list[str]

Return the band ids in declaration order.

bands: list[BandSpec]

bit_depth: int

gsd: float

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

profile_id: str

profile_version: str

sensor_id: str

msi_processor.sensors.profile.load_profile(path)

Load and validate a sensor profile JSON instance.

Return type:

SensorProfile

Parameters:

path:

Filesystem path to the profile JSON.

Returns:

SensorProfile

The validated, typed profile.

Raises:

ProfileValidationError

If the file is missing, not valid JSON, or fails schema validation (REQ-DAT-03).